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Building a Chatbot on a Closed Domain using RASA

Authors:

Khang Nhut Lam,

Nam Nhat Le,

Jugal KalitaAuthors Info & Claims

NLPIR '20: Proceedings of the 4th International Conference on Natural Language Processing and Information Retrieval

Pages 144 - 148

https://doi.org/10.1145/3443279.3443308

Published: 01 February 2021 Publication History

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Abstract

In this study, we build a chatbot system in a closed domain with the RASA framework, using several models such as SVM for classifying intents, CRF for extracting entities and LSTM for predicting action. To improve responses from the bot, the kNN algorithm is used to transform false entities extracted into true entities. The knowledge domain of our chatbot is about the College of Information and Communication Technology of Can Tho University, Vietnam. We manually construct a chatbot corpus with 19 intents, 441 sentence patterns of intents, 253 entities and 133 stories. Experiment results show that the bot responds well to relevant questions.

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Index Terms

Building a Chatbot on a Closed Domain using RASA
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Question answering

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NLPIR '20: Proceedings of the 4th International Conference on Natural Language Processing and Information Retrieval

December 2020

217 pages

ISBN:9781450377607

DOI:10.1145/3443279

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 February 2021

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NLPIR 2020: 4th International Conference on Natural Language Processing and Information Retrieval

December 18 - 20, 2020

Seoul, Republic of Korea

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Chatbot with Touch and Graphics: An Interaction of Users for Emotional Expression and Turn-taking

Chatbot Theory: A Naïve and Elementary Theory for Dialogue Management

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